Open AccessPenerapan Metode Data Mining Pada Point of Sale Berbasis Web Menggunakan Algoritma Apriori
Author(s) -
Adam Firmansyah,
Muhammad Wahyudin,
Ben Rahman
Publication year - 2021
Publication title -
jurnal media informatika budidarma/jurnal media informatika budidarma
Language(s) - English
Resource type - Journals
eISSN - 2614-5278
pISSN - 2548-8368
DOI - 10.30865/mib.v5i3.3085
Subject(s) - apriori algorithm , association rule learning , point of sale , statement (logic) , value (mathematics) , a priori and a posteriori , computer science , point (geometry) , data mining , customer value , mathematics , world wide web , machine learning , philosophy , geometry , hierarchy , epistemology , political science , economics , law , market economy
To be able to understand which products have been purchased by customers, it is done by describing the habits when customers buy. Use association rules to detect items purchased at the same time. This study uses an a priori algorithm to determine the association rules when buying goods. The results of the study and analyzing the data obtained a statement that using the a priori algorithm to select the combined itemset using a minimum support of 25% and a minimum confidence of 100%, found the association rule, namely, if the customer buys at the same time. Buying goods has the highest value of support and trust. Likewise with the support value of 25%, the confidence value is 100%. In this way, if a customer buys an item, the probability that the customer buys the item is 100%